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Scientists unveil starfish-inspired wearable tech for heart monitoring

Designed by University of Missouri researchers, the device includes AI technology to detect potential heart problems with over 90% accuracy, making it a promising tool for at-home monitoring

Scientists unveil starfish-inspired wearable tech for heart monitoring
2025-04-02
(Press-News.org) When we move, it’s harder for existing wearable devices to accurately track our heart activity. But University of Missouri researchers found that a starfish’s five-arm shape helps solve this problem. 

Inspired by how a starfish flips itself over — shrinking one of its arms and using the others in a coordinated motion to right itself — Sicheng Chen and Zheng Yan in Mizzou’s College of Engineering and collaborators have created a starfish-shaped wearable device that tracks heart health in real time. 

Because the starfish-inspired device has multiple points touching the skin near the heart, it stays more stable than traditional wearables built as a single, unified structure, such as a smartwatch. This allows the device to collect clearer, more accurate heart data — even while someone is moving.

The device conveniently pairs with a smartphone app to provide the user with health insights and help detect potential heart problems.

“Similar to a starfish, our device has five arms, each equipped with sensors that simultaneously capture both electrical and mechanical heart activity,” Chen, a postdoctoral fellow and lead author, said. “Most current devices focus on capturing only one signal or require separate devices to track multiple signals at the same time. This allows us to provide a more complete picture of someone’s heart health.”

AI for smarter heart monitoring

The team developed an artificial intelligence-powered system that learned from a large collection of heart data, including signals from both healthy individuals and people with heart disease. Using smart technology, the system filters out movement-related disruptions and analyzes heart signals to determine if someone’s heart is healthy or showing signs of trouble. The findings are shown on the smartphone app. 

This AI-based approach correctly identifies heart conditions more than 90% of the time. Because the device has Bluetooth capability, doctors can review the data remotely, making it a convenient option for at-home monitoring between medical visits.

"This is also a benefit over traditional clinical heart tests such as the Doppler ultrasound, which usually requires patients to stay still to get accurate results," Chen said.

Designed for comfort and long-term use

The team is also improving the long-term wearability of these devices. 

“A big challenge with wearable devices is that they can cause skin irritation when worn for long periods,” Yan, an associate professor in Mizzou’s College of Engineering, said.

To address this, Yan’s team is working on making the device more comfortable and skin friendly. Right now, the device sticks to the skin using a special gel, but future versions will use a breathable, skin-friendly material for more comfort. Yan’s team has been improving this material for the past few years.

The starfish-inspired device can also charge wirelessly while still being worn, ensuring continuous use without needing to remove it for charging.

While still in early development, the starfish-inspired innovation brings together nature, engineering and AI in a way that could change how we manage heart health — making it easier and more reliable for people to track their heart activity anytime, anywhere.

“Starfish-inspired wearable bioelectronic systems for physiological signal monitoring during motion and real-time heart disease diagnosis,” was published in the journal Science Advances. Other co-authors are Qunle Ouyang, Xuanbo Miao Zehua Chen and Ganggang Zhao at Mizzou.

END

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[Press-News.org] Scientists unveil starfish-inspired wearable tech for heart monitoring
Designed by University of Missouri researchers, the device includes AI technology to detect potential heart problems with over 90% accuracy, making it a promising tool for at-home monitoring